The San Francisco Bay Area, California, is a nine-county metropolitan area that surrounds the San Francisco Bay estuary. The Bay Area has a population of over 7 million including the cities of San Francisco, San Jose and Oakland, and is the fifth largest metropolitan area in the United States. is a map of the Bay Area including sub-basins within the Bay. The estuary is the outlet of the Sacramento and San Joaquin Rivers, which drain California's Central Valley representing 40% of the entire area of the State.
Map of the San Francisco Bay Area. The dashed line represents the approximate boundaries of the model domain.
Regional environmental properties and associated uncertainties, expressed as confidence factors, used as inputs to the mercury fate and transport model are shown in . The confidence factor (Cf) defines the 95% confidence limits around a median value for each input parameter due to uncertainty and variability. We estimate this factor assuming that the parameter variance due to variability and uncertainty can be represented by a lognormal distribution (19
). Thus, 95% of the possible values for a given parameter (P) fall between P/Cf and P×Cf.
Regional environmental properties and 95% confidence factors (Cf) for the San Francisco Bay Area Region (MTC: mass transfer coefficient).
The modeled regional environment is defined by the watershed boundaries for the San Francisco Bay estuary except for the Sacramento and San Joaquin Rivers, which enter the model domain at the eastern end of Suisun Bay (). Because of the importance of the estuary as a defining feature of the Bay Area regional environment, the availability of extensive monitoring data (25
) and the use impairments caused by the fish consumption advisories, significant effort was devoted to selecting optimal parameters and confidence factors to describe the hydrodynamics and sediment budget of the Bay.
In parameterizing the model with region-specific data we faced a trade-off between complexity and reliability. The available information on mercury concentrations and loadings and the current understanding of mercury kinetics in the estuary favored a single-region model as optimum for transparently assessing the overall mass balance in the system. But the use of a single region model for an estuary with a high degree of variability in environmental conditions complicates the specification of some of the landscape and hydrologic parameters that characterize this system. The key advantage of a single region model is transparent compilation of the mass balance and the ability to perform an uncertainty analysis to characterize the influence of highly variable and/or uncertain input parameters. The model therefore provides an initial mass balance that can be refined as necessary.
Of particular note is the value of the single-region model for assessing the descriptive power of the model framework and for evaluating the impact of future refinements to the model and/or to the quantity and quality of available data. This approach allows us to prioritize new data to produce the most efficient reduction in uncertainty of the model outputs. A disadvantage of the single-region model is that it requires selection of a single “best estimate” value to describe an estuary with characteristics that are highly variable in space and time in the real system. For example, some areas of the Bay are experiencing net deposition of sediments from the water column, while others are undergoing net erosion (27
). Similarly, the concentration of suspended sediments in the water column varies over more than two orders of magnitude between areas near the outlet of major rivers and the mouth of the Golden Gate (25
). As a result, the confidence factors for input parameters must be selected to describe characteristics of the estuary that are highly spatially variable. We based the average sediment budget for the estuary used in the model on the work of Krone (26
). The water and sediment budgets have been harmonized so that the hydrodynamics of the system are at steady state, ie, the net flows of water and sediment into the system are balanced by flows out of the system, and burial in the case of sediment solids.
Regional Mercury Emissions
Mercury enters active circulation in the San Francisco Bay area environment by (a) direct local emissions, (b) advective inflow in the atmosphere and from the Central Valley rivers (c) re-mobilization of contaminated sediments and (d) erosion of mercury-containing soils. Suisun Bay and San Pablo Bay are repositories for contaminated sediments that were deposited in the 1850s through the 1880s from hydraulic mining operations in the Sierra Nevada Mountains. Hydraulic mining techniques used at this time required large volumes of water to strip hillsides of soil. Gold was extracted from the resulting slurry by settling in sluices lined with elemental mercury that captured fine gold particles (29
). The legacy of these operations is mercury contamination in the sediments of the San Francisco estuary as well as the sediments upstream in the San Joaquin and Sacramento watersheds. Therefore major sources of mercury for the San Francisco Region include releases from sediments in the estuary and from sediments upstream that enter the Bay through the Sacramento and San Joaquin Rivers. In addition to historically elevated levels of mercury in estuary and river sediments, the hills immediately surrounding the estuary have naturally high concentrations of mercury and the area was home to mercury mining operations up to the 1970s (15
As part of its development of an estimated Total Maximum Daily Load (TMDL) for mercury to the San Francisco Bay Estuary, the California Regional Water Control Board has estimated current mercury sources to the Bay Area. Direct loading estimates for the San Francisco Bay estuary and their associated uncertainty ranges were first reported to the US EPA on June 30, 2000 (20
). Estimates of loading to the San Francisco Bay estuary were revised to be slightly lower in a more recent TMDL report (15
). For the purposes of this modeling exercise the most recent loading estimates have been used with uncertainty ranges estimated from data presented in both reports. The flux of MeHg entering the Bay from the Sacramento and San Joaquin Rivers is taken from the study by Cloe and Gill (30
). Emission estimates are summarized in .
Table 2 Mercury emission parameters for the San Francisco Bay Area (Cf — 95% confidence factor) (15,20,30,31)
Direct mercury inputs to the atmosphere in the San Francisco Bay Area have been estimated to be 370 kg total mercury per year from a combination of stationary and mobile combustion sources, breakage of consumer products such as fluorescent lamps, and emissions from abandoned mine sites (20
). The speciation of mercury released to the atmosphere is not specified in the TMDL reports (15
); therefore we assume that 100% of local mercury sources to the atmosphere are in the form of elemental mercury. In addition, air entering the Bay Area air basin is assumed to be contaminated with total mercury at a concentration of 2.1 ± 0.8 ng/m3
, reflecting the background contaminant burden due to large-scale cycling of natural and anthropogenic mercury (31
Regional Mercury Concentrations in the Environment and Biota
Total mercury concentrations in water, sediment and bivalves in the San Francisco Bay estuary have been monitored since 1993 by the Regional Monitoring Program (RMP) under the direction of the San Francisco Estuary Institute (25
). Total mercury concentrations in the San Francisco Bay ecosystem have not shown any discernable temporal trend during this ten-year monitoring program, indicating that the system is currently near steady-state. In 2000 the RMP began monitoring methyl mercury as well as total mercury in the estuary. Median total mercury and methyl mercury concentrations from the RMP data set averaged over the whole bay are shown in along with 95% confidence factors of observed concentrations from different sites and different sampling years.
Reported mercury concentrations and fluxes in the Bay Area Region and associated 95% confidence factors (Cf).
Tsai and Hoenicke (31
) reported mercury concentrations in ambient air from three sites in the San Francisco Bay area during the year 2000 and estimated the depositional flux of mercury to the estuary. Median concentrations observed in this study and confidence factors are also shown in , along with their estimate of the depositional flux from the atmosphere.
Partition Coefficients and Concentration Ratios for Mercury Species
In , we provide values of dimensionless partition coefficients and concentration ratios, and their associated confidence factors, for the three mercury species groups. When possible, we have estimated partition coefficients and concentration ratios from measurement data gathered in the San Francisco Bay Area region. In this regard, the model has been “tuned” to provide the most accurate possible description of partitioning and speciation of mercury in the SFBE system.
Partition coefficients (K) and species concentration ratios for mercury in the San Francisco Bay Area and associated 95% confidence factors (Cf)
Model Uncertainty Analysis and Model Evaluation
Because models are developed for specific purposes, they are not “true” or “valid” in a general sense, but become useful by accumulating confidence through calibration, verification, and evaluation exercises. In this section, we explain the process we used to characterize the uncertainty in the model results and to evaluate its performance relative to available benchmark measurements. We carried out an uncertainty analysis using standard error propagation methods and evaluated model performance against observed mercury concentrations in the San Francisco Bay region.
Uncertainty analysis of the model's description of mercury fate in the Bay Area was carried out by Monte Carlo analysis using the confidence factors shown in , and to represent uncertainty and variability in input parameters. We used the Crystal Ball® Software package with 5000 trials and standard Monte Carlo sampling to propagate input variance to outcome variance. We used the results of this process to construct the range and likelihood of media-specific mercury species concentration values. In and we compare modeled and measured 95% confidence intervals for ΣHg and MeHg concentrations in the Bay Area. In we compare our model estimate of the depositional flux of ΣHg to the estuary with the previous estimate made by Tsai and Hoenicke (31
). The diagonal line in and is provided for reference indicating a 1:1 relationship between the modeled and observed concentrations and fluxes of Hg in the system.
Comparison of modeled and observed concentrations and fluxes of total mercury in the Bay Area.
Comparison of modeled and observed concentrations of methyl mercury in the Bay Area.
and indicate that the model is providing a satisfactory overall description of mercury loadings, fate and transport in the Bay Area region that is consistent with observations. In all cases the 95% confidence interval in the model results overlaps the 95% confidence interval in the observed concentrations, or the previous estimate of depositional flux of total mercury.
It is noteworthy that the confidence intervals in both the model results and the measurement data are wide, spanning over 2 orders of magnitude in some cases for ΣHg, and in all cases for the MeHg species group. These large confidence intervals are a result of the spatial and temporal heterogeneity of the estuary system and uncertainty and variability associated with the Bay-wide suspended particle and sediment balance. The single water compartment in the model averages depositional zones near the major river inputs and oceanic conditions at the mouth of the Golden Gate. Because of this variability in conditions, the variance in suspended particulate concentration (an input to the model) is estimated at a factor of 16. The active depth of sediments in the Bay is another highly uncertain and variable input parameter that drives the wide confidence intervals in the model outputs. The central estimate of active sediment mixing depth (15 cm) is based on a value selected for a similar model applied to PCBs (22
), and a single study at one location in the San Francisco Bay (33
). It is assigned a confidence factor of 3 to represent uncertainty associated with estimating a value from only one measurement, and variability in sediment bed shear throughout the system.
Species-Specific Mass Balances for Mercury
shows steady-state mass balance diagrams for Hg0, the Hg2+ species group, the MeHg species group, and for ΣHg, using the median values of all input parameters. Fluxes are shown in kg/year and summed for each process to calculate fluxes of ΣHg. Inspection of shows that the dominant fate and transport processes differ considerably for the three species groups of mercury.
Figure 5 Steady-state mass balance of elemental mercury (Hg0), divalent mercury species (Hg2+), methylmercury species (MeHg) and total mercury (ΣHg) in the San Francisco Bay Area. Fluxes are rounded to the nearest 1 kg/y or 4 significant digits. Percentages (more ...)
The model mass balance indicates that elemental mercury loading to the San Francisco Bay Region is dominated by inflow of background air, which contributes over 50 times more mercury loading than local emissions to the atmosphere. However, background inflow is balanced by advection out of the region, which slightly exceeds inflow indicating that the Bay Area region provides a net input of atmospheric Hg0
to the global environment. After direct emission, the most important regional contribution of Hg0
to the atmosphere is volatilization from vegetation. The modeled mass balance indicates that divalent mercury (Hg2+
) species are taken up by vegetation from soils and as a result of particulate deposition from the atmosphere. The Hg2+
is then converted to Hg0
in the vegetation compartment and subsequently volatilized to the atmosphere. Leonard et al. (16
) have examined the possible role of vegetation as a pathway for mercury evasion from contaminated soils to the atmosphere. Our proposed model also indicates that vegetation may act as a medium for the conversion of Hg2+
species into Hg0
, which is then subject to global-scale transport in the atmosphere.
Despite the large fluxes through the atmosphere, the largest single reservoir of Hg0 in the San Francisco Bay regional environment is in the sediment compartment. The model suggests elemental mercury is produced in sediments by conversion from Hg2+ species that were deposited on particles from the water column. Net production in sediments drives a flux of Hg0 from sediment to water, where it is converted back to Hg2+ species. Volatilization of Hg0 from the Bay to the atmosphere is approximately balanced by atmospheric deposition. Although the model indicates that a high percentage of the Hg0 burden in the region resides in soil and sediment, the concentration of Hg0 in these compartments is very low relative to Hg2+, as indicated by the concentration ratios shown in .
Similarly to Hg0
, there is a significant flux of Hg2+
species through the Bay Area region in the atmosphere. The dominant deposition process from the atmosphere for the entirely particle-associated Hg2+
species is scavenging by vegetation. However, atmospheric deposition of Hg2+
species is a very minor component of total loadings to the estuary, which are dominated by the sources identified in the TMDL reports (15
). The sediments of the estuary house the bulk of the regional inventory. In the aquatic system the most prominent feature of Hg2+
fate is cycling between the water column and sediments. An average Hg2+
atom undergoes 10 cycles of deposition and re-suspension during its residence time in the Bay. As a result of the close coupling between the water and sediment system re-suspension is the dominant source to the water compartment, indicating contamination in the sediments is controlling Hg2+
concentrations in estuary water.
Methylated mercury species are of particular concern in aquatic ecosystems because of their tendency to bioaccumulate to unacceptably high levels in food webs. The Bay Area regional mass balance indicates that a small net production of MeHg species occurs in sediments (). Methylmercury production in sediments is consistent with bacterial methylation of Hg2+
species. The net methylation rate calculated by the model sediment is small, less than 2 kg/year. If substantial methylation is occurring in wetlands within the Bay the model indicates that it is approximately balanced by demethylation reactions in other parts of the system. This interpretation is consistent with Choe and Gill (30
), who estimated 0.6 kg/year net destruction of monomethyl mercury in the northern reach of San Francisco Bay based on analysis water samples at different locations.
The mass balance of ΣHg in the Bay Area is determined almost entirely by the dynamics of the Hg2+ species group, the most prevalent species group in all compartment of the system except the atmosphere. There is net atmospheric deposition of ΣHg to soils and water in the region, while deposition to vegetation is approximately balanced by revolatilization of Hg0. Because of the large flux of Hg0 through the atmosphere the overall regional residence time of ΣHg is only 6.3 years, however residence time in the estuary is much longer (~50 years), and is determined by the residence time of Hg2+ associated with sediments in the system.
The results of the uncertainty analysis () illustrate the controlling influence of sediment dynamics on the fate and transport of mercury in the estuary. Aside from the rate of direct emission of Hg2+ species to water, the model parameters that control variance in calculated mercury concentrations in water and sediment in the estuary are all parameters associated with the description of the sediment budget of the system. In particular, the response time of the water-sediment system to changes in mercury loading is controlled to a large extent by the active sediment layer mixing depth and the relative rates of sediment burial versus removal to the ocean by resuspension and advection in bulk water. To a large extent, the uncertainties associated with the current model are determined by uncertainty and variability associated with attempting to assign single, Bay-wide estimates to these parameters.
Percent contribution to variance in modeled total mercury concentrations and persistence in the San Francisco Bay Estuary.
The current model is relatively simple in form, and is designed to provide an overall accounting of sources and sinks in the San Francisco Bay region. The lack of spatial resolution introduces a high degree of variance in calculated mercury concentrations because of the spatial heterogeneity of the real system. The model has, however, demonstrated reliability in making large scale mass balance estimates for mercury in a way that allows policy makers to understand the relative importance of various emissions sources and loss mechanisms. In many modeling studies of this type data available for model evaluation are the limiting factor determining the spatial resolution of the assessment. In this case, the quality and quantity of monitoring data becoming available from the San Francisco Estuary Institute RMP program provide future opportunities to refine the current model by introducing more spatial resolution within the Estuary. With sufficient calibration data, a spatially resolved model could reduce uncertainties in model results and provide mercury concentrations and response times to changes in loadings for sub-basins within the Bay. Moreover, because the imports from the Sacramento River are attributable to historical loads in the sediments of the Sacramento and San Joaquin catchments there is a need to incorporate the long-term behavior of these river systems in future modeling efforts.
The development of a reliable spatially resolved mercury mass balance model for the San Francisco estuary system will require site-specific studies of sediment dynamics in the system. Without this information spatial resolution cannot reduce total variance in model results. Sediment dynamics studies that provide a more refined understanding of active sediment layer depth and sediment deposition and re-suspension rates will also contribute to improved understanding of the dynamics of other particle associated contaminants in the system, such as highly chlorinated polychlorinated biphenyls (22
We suggest that the first priority for refining the current model is increasing the spatial resolution in the estuary system. Future models might also include a kinetic description of species inter-conversion reactions; however the option to retain the assumption of constant species concentration ratios in model compartments should be retained. This assumption makes the modeling process much easier to manage and avoids the need for rate constants that describe media specific transformations among the species groups. Since these rate constants are not currently available a model that requires these parameters will have large inherent uncertainties. Therefore a refined model that adds both more spatial resolution and a kinetic description of species inter-conversion could actually increase rather than decrease uncertainty.
In summary, the regional fate and transport model presented here successfully reconciles identified sources with observed concentrations of total mercury and methyl mercury in the San Francisco Bay area. The mass balance provided by the model indicates that continental and global background mercury concentrations control levels in the atmosphere of the Bay Area, but have little impact on surface water concentrations of total mercury in the estuary. Loadings to the San Francisco estuary are dominated by runoff from the Central Valley and re-mobilization of contaminated sediments deposited during past mining activities. Moreover the imports from the Sacramento Rivers are attributable to historical loads in the sediments of the Sacramento and San Joaquin water sheds. The model framework developed here is general, and can be applied to other systems to test its robustness, including systems where mercury inputs are dominated by atmospheric deposition.